Building a Digital Respiratory Disease Framework for COPD management in Central Appalachia

项目概要/摘要 与城市居民相比，农村社区慢性阻塞性肺疾病患病率更高 慢性阻塞性肺疾病（COPD）的疾病控制较差，导致发病率和死亡率较高。总的来说，农村居民 贫困率和无保险率较高，再加上地理位置偏僻和交通不便， 高质量的医疗保健。这一点和其他社会因素导致了更高的发病率和更差的结果， 几乎所有的慢性病。远程保健有望解决这些挑战，并扩大获得 专家护理，但定性远程保健访问往往缺乏必要的病人数据， 医生做出明智的管理决策。远程医疗也经常受到有限宽带的阻碍 农村地区的准入。用于远程监控的可穿戴技术也受到类似的限制， 以及繁重的日常参与要求，导致老年人、病情较重人群的依从率较低。 为了应对这些挑战，Medentum正在开发一种负担得起的，可访问的，多功能的家庭使用 该设备具有摄像头、低成本传感器（温度、脉搏血氧计）和数字听诊器。一 配套的手机应用程序允许记录人口统计数据，社会文化数据，病史， 症状，并指导患者用手持设备收集他们的生物特征读数。未经 宽带的必要性，患者可以安全地将他们的信息传输给远程医生/慢性病 可以制定诊断和治疗计划专家。对于这个SBIR，Medentum将调整其设备， 呼吸系统疾病的软件平台，将其与人工智能（AI）算法分层， 呼吸系统疾病框架（DRDF），使COPD的自我管理。该SBIR的目标是 1)在阿巴拉契亚中部农村人群中研究COPD呼吸系统框架的可用性和可行性 弗吉尼亚州西南部的75名患者，2）建立初步的人工智能算法，自主预测COPD 通过分析包括风险因素（社会、行为、环境）在内的低负担变量， 症状、COPD评估测试和设备生物特征（体温、脉搏、血氧饱和度、呼吸 频率和呼吸音）。在第二阶段，该平台将纳入智能触发器，如果确定 满足环境风险因素，促使他们与平台互动。智能算法将 自动预测他们的COPD恶化风险，最终将他们分流到适当的治疗。预测 通过促进早期与医疗提供者的联系， 有效的治疗将对农村COPD的健康结果和治疗费用产生巨大影响 患者最终，该平台将增强COPD自我管理，促进预防性呼吸护理， 并传播基于证据的COPD治疗，所有这些都旨在减少 偏远，服务不足的阿巴拉契亚中部人口，呼吸结果更差。

PROJECT SUMMARY/ABSTRACT Compared to urban residents, rural communities have higher rates of chronic obstructive pulmonary disease (COPD) with worse disease control, resulting in higher rates of morbidity and mortality. In general, rural residents suffer from higher poverty and uninsured rates, further compounded by geographic isolation and limited access to quality healthcare. This and other social factors have resulted in higher incidence and worse outcomes of nearly every chronic disease. Telehealth holds promise to address these challenges and expand access to specialist care in these communities, but qualitative telehealth visits often lack necessary patient data for physicians to make informed management decisions. Telemedicine is also often hindered by limited broadband access in rural areas. Wearable technologies for remote monitoring suffer similar limitations, and, due to cost and burdensome daily engagement requirements, lead to poor adherence rates in an older, sicker population. To address these challenges, Medentum is developing an affordable and accessible, multi-functional, home-use device featuring a camera, low-cost sensors (temperature, pulse oximeter) and a digital stethoscope. A companion phone application allows the recording of demographics, sociocultural data, medical history, and symptoms, and guides the patient to collect their biometric readings with the handheld device. Without the necessity of broadband, the patient can transmit their information securely to a remote physician/chronic disease specialist who can make a diagnosis and treatment plan. For this SBIR, Medentum will adapt its device and software platform for respiratory disease, layering it with artificial intelligence (AI) algorithms, to create a digital respiratory disease framework (DRDF) that empowers self-management of COPD. The aims of this SBIR are to 1) study the usability and feasibility of this COPD respiratory framework in a rural Central Appalachian population of 75 patients in Southwest Virginia and 2) build preliminary AI algorithms that autonomously predict COPD exacerbation risk by analyzing low burden variables including risk factors (social, behavioral, environmental), symptoms, COPD Assessment tests, and device biometrics (temperature, pulse, oxygen saturation, respiration rate and breath sounds). In Phase II, the platform will incorporate smart triggers that will alert patients if certain environmental risk factors are met, prompting them to engage with the platform. The smart algorithms will then automatically predict their COPD exacerbation risk, ultimately triaging them to appropriate treatment. Predicting and pre-empting disease exacerbation by facilitating early connections to medical providers for prompt and effective treatment will have an enormous impact on health outcomes and treatment costs for rural COPD patients. Ultimately, this platform will augment COPD self-management, promote preventive respiratory care, and disseminate evidence-based COPD treatments, all designed to reduce the significant health disparities in a remote, underserved Central Appalachian population with worse respiratory outcomes.